<table border="0" width="*">
<caption>Group A: Coefficients for Distance to Elementary School Variables</caption>
<tr><td colspan=7><hr></td></tr>
<tr><td>                              </td><td> weight <= 4700              </td><td> weight <= 4500              </td><td> weight <= 4300              </td><td> weight <= 4100              </td><td> weight <= 3900              </td><td> weight <= 3700              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}miles per gallon</td><td>         -112.7              </td><td>         -112.7              </td><td>         -113.0              </td><td>         -183.7<sup>***</sup></td><td>         -207.6<sup>***</sup></td><td>         -177.5<sup>***</sup></td></tr>
<tr><td>                              </td><td>         (71.9)              </td><td>         (71.9)              </td><td>         (72.3)              </td><td>         (64.9)              </td><td>         (65.9)              </td><td>         (44.0)              </td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}rep78 is 2</td><td>          342.7              </td><td>          342.7              </td><td>          462.2              </td><td>          773.2              </td><td>          820.8              </td><td>          306.7              </td></tr>
<tr><td>                              </td><td>       (1798.0)              </td><td>       (1798.0)              </td><td>       (1815.1)              </td><td>       (1584.0)              </td><td>       (1581.6)              </td><td>       (1062.8)              </td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}rep78 is 3</td><td>          680.1              </td><td>          680.1              </td><td>          716.5              </td><td>          492.5              </td><td>          389.6              </td><td>          116.4              </td></tr>
<tr><td>                              </td><td>       (1677.9)              </td><td>       (1677.9)              </td><td>       (1686.6)              </td><td>       (1469.4)              </td><td>       (1451.2)              </td><td>        (955.1)              </td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}rep78 is 4</td><td>         1377.5              </td><td>         1377.5              </td><td>         1439.9              </td><td>         1556.6              </td><td>         1771.1              </td><td>         1412.8              </td></tr>
<tr><td>                              </td><td>       (1741.1)              </td><td>       (1741.1)              </td><td>       (1751.6)              </td><td>       (1527.5)              </td><td>       (1523.0)              </td><td>       (1000.9)              </td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}rep78 is 5</td><td>         3010.3<sup>*</sup>  </td><td>         3010.3<sup>*</sup>  </td><td>         3022.0<sup>*</sup>  </td><td>         3121.0<sup>*</sup>  </td><td>         3223.1<sup>**</sup> </td><td>         2550.7<sup>**</sup> </td></tr>
<tr><td>                              </td><td>       (1784.4)              </td><td>       (1784.4)              </td><td>       (1792.7)              </td><td>       (1561.2)              </td><td>       (1539.5)              </td><td>       (1013.5)              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td>N                             </td><td>             67              </td><td>             67              </td><td>             66              </td><td>             64              </td><td>             60              </td><td>             55              </td></tr>
<tr><td>incdgr4500                    </td><td>            Yes              </td><td>            Yes              </td><td>             No              </td><td>             No              </td><td>             No              </td><td>             No              </td></tr>
<tr><td>incdgr4000                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>             No              </td><td>             No              </td></tr>
<tr><td>incdgr3500                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td></tr>
<tr><td>incdgr3000                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td colspan=7>
* 0.10 ** 0.05 *** 0.01. Standard Errors clustered at village level. Each Column is a spearate regression.
</td></tr>
</table>
<table border="0" width="*">
<caption>Group B: Coefficients for Elementary School Physical Quality Variables</caption>
<tr><td colspan=7><hr></td></tr>
<tr><td>                              </td><td> weight <= 4700              </td><td> weight <= 4500              </td><td> weight <= 4300              </td><td> weight <= 4100              </td><td> weight <= 3900              </td><td> weight <= 3700              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}headroom variable</td><td>         -652.0              </td><td>         -652.0              </td><td>         -625.4              </td><td>         -594.4              </td><td>         -547.5              </td><td>         -474.7              </td></tr>
<tr><td>                              </td><td>        (478.5)              </td><td>        (478.5)              </td><td>        (478.3)              </td><td>        (435.1)              </td><td>        (432.4)              </td><td>        (320.6)              </td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}miles per gallon</td><td>          -99.3              </td><td>          -99.3              </td><td>          -95.0              </td><td>         -155.6<sup>**</sup> </td><td>         -176.3<sup>***</sup></td><td>         -156.0<sup>***</sup></td></tr>
<tr><td>                              </td><td>         (70.3)              </td><td>         (70.3)              </td><td>         (70.3)              </td><td>         (65.3)              </td><td>         (65.9)              </td><td>         (48.1)              </td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}this is the trunk variable</td><td>           9.91              </td><td>           9.91              </td><td>           2.95              </td><td>           60.3              </td><td>           42.0              </td><td>           68.3              </td></tr>
<tr><td>                              </td><td>        (107.6)              </td><td>        (107.6)              </td><td>        (107.6)              </td><td>         (98.4)              </td><td>         (98.3)              </td><td>         (75.6)              </td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}and here the weight variable</td><td>           1.21              </td><td>           1.21              </td><td>           1.39              </td><td>           0.84              </td><td>           0.97              </td><td>           0.96              </td></tr>
<tr><td>                              </td><td>         (0.89)              </td><td>         (0.89)              </td><td>         (0.91)              </td><td>         (0.84)              </td><td>         (0.83)              </td><td>         (0.62)              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td>N                             </td><td>             72              </td><td>             72              </td><td>             71              </td><td>             69              </td><td>             65              </td><td>             60              </td></tr>
<tr><td>incdgr4500                    </td><td>            Yes              </td><td>            Yes              </td><td>             No              </td><td>             No              </td><td>             No              </td><td>             No              </td></tr>
<tr><td>incdgr4000                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>             No              </td><td>             No              </td></tr>
<tr><td>incdgr3500                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td></tr>
<tr><td>incdgr3000                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td colspan=7>
* 0.10 ** 0.05 *** 0.01. Standard Errors clustered at village level. Each Column is a spearate regression.
</td></tr>
</table>
<table border="0" width="*">
<caption>Group C: More Coefficientss</caption>
<tr><td colspan=7><hr></td></tr>
<tr><td>                              </td><td> weight <= 4700              </td><td> weight <= 4500              </td><td> weight <= 4300              </td><td> weight <= 4100              </td><td> weight <= 3900              </td><td> weight <= 3700              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td>\vspace*{0mm}\hspace*{2mm}variable is turn</td><td>         -185.7              </td><td>         -185.7              </td><td>         -176.7              </td><td>         -239.7<sup>**</sup> </td><td>         -233.8<sup>*</sup>  </td><td>         -245.2<sup>**</sup> </td></tr>
<tr><td>                              </td><td>        (128.1)              </td><td>        (128.1)              </td><td>        (128.3)              </td><td>        (119.5)              </td><td>        (123.7)              </td><td>         (96.6)              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td>N                             </td><td>             72              </td><td>             72              </td><td>             71              </td><td>             69              </td><td>             65              </td><td>             60              </td></tr>
<tr><td>incdgr4500                    </td><td>            Yes              </td><td>            Yes              </td><td>             No              </td><td>             No              </td><td>             No              </td><td>             No              </td></tr>
<tr><td>incdgr4000                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>             No              </td><td>             No              </td></tr>
<tr><td>incdgr3500                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td></tr>
<tr><td>incdgr3000                    </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td><td>            Yes              </td></tr>
<tr><td colspan=7><hr></td></tr>
<tr><td colspan=7>
* 0.10 ** 0.05 *** 0.01. Standard Errors clustered at village level. Each Column is a spearate regression.
</td></tr>
</table>
